Cancer-associated fibroblast subtype and risk signature as predictors of prognosis and treatment effectiveness in gastric cancer

Despite the persistent high incidence and mortality rates of gastric cancer, limited progress has been made in improving prognosis.cancer-associated fibroblasts (CAFs) hold promise as novel biomarkers, yet their specific roles and mechanisms in gastric cancer remain enigmatic. We utilized the TCGA-STAD dataset for model training and the GSE84433 dataset for validation to explore potential associations between cancer-associated fibroblasts (CAFs) and clinical outcomes in gastric cancer. Through consensus clustering, differential expression analysis, enrichment analysis, and immune infiltration assessment, Kaplan-Meier (KM) survival analysis, and TIMER database exploration, we examined the prognostic significance and underlying biological mechanisms of CAF-related genes in gastric cancer. A CAF risk model (CAF-RM) was developed to assess the correlation between risk scores and survival, drug sensitivity, and immune infiltration. The model was further validated through immunohistochemical (IHC) and immunofluorescence (IF) staining. Utilizing data from 42 CAF-related genes, consensus clustering identified two distinct patient subgroups, C1 and C2, with significant differences in survival, immune scores, and immune cell infiltration. A Cox-Lasso regression-derived CAF-RM accurately discriminated high-risk from low-risk gastric cancer patients, consistent with validation cohort results, IHC and IF staining. These findings suggest that CAFs play a role in the tumor immune microenvironment of gastric cancer and highlight the efficacy of CAF-RM in prognosis prediction. CAF subtypes associate with immune tumor microenvironment alterations in gastric cancer. The validated CAF risk model predicts patient survival, immune infiltration, and drug sensitivity, enhancing understanding of CAFs and guiding gastric cancer therapy.